task analysis lavaggio denti

Task Analysis Lavarsi i Denti: La Guida Definitiva per una Perfetta Igiene Orale

task analysis lavarsi i denti

Lavarsi i denti è un’attività quotidiana importante per garantire una corretta igiene orale. In questa task analysis, esamineremo i passaggi chiave per eseguire efficacemente questa azione.

1. Preparazione: Prima di iniziare a lavarsi i denti, è fondamentale raccogliere tutto il necessario. Prendete lo spazzolino da denti, il dentifricio e un bicchiere d’acqua.

2. Bagnare lo spazzolino: Prima di applicare il dentifricio, bagnate lo spazzolino sotto l’acqua corrente. Questo aiuta ad attivare le setole e a rendere più facile la pulizia.

3. Applicare il dentifricio: Squeeze out a pea-sized amount of toothpaste on the bristles of your toothbrush. La quantità di dentifricio necessaria è una piccola quantità simile a un pisello. Gli adulti dovrebbero usare un dentifricio con fluoruro per una protezione extra contro le carie.

4. Spazzolare i denti: Iniziate spazzolando delicatamente i denti, muovendo lo spazzolino in modo circolare. Assicuratevi di spazzolare sia la parte anteriore che quella posteriore dei denti, così come le superfici masticatorie. Concentratevi anche sulle gengive per rimuovere la placca e prevenire la gengivite. La durata consigliata per lo spazzolamento è di almeno due minuti.

5. Risciacquare correttamente: Dopo aver spazzolato i denti, risciacquate bene la bocca con acqua. Assicuratevi di eliminare completamente il dentifricio e i residui.

6. Pulizia della lingua: Non dimenticate di pulire anche la lingua per rimuovere i batteri che possono causare alitosi. Utilizzate uno spazzolino per la lingua o uno strumento apposito per raschiarla delicatamente.

7. Sciacquare il bicchiere: Dopo aver completato il lavaggio dei denti, sciacquate bene il bicchiere d’acqua utilizzato. Rimuovere gli eventuali residui di dentifricio o saliva.

Seguendo questa task analysis, sarete in grado di lavarvi i denti in modo efficace e mantenere una corretta igiene orale. Ricordate di spazzolare i denti almeno due volte al giorno, preferibilmente dopo i pasti, per garantire una salute orale ottimale.

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Il chaining: insegnare i comportamenti complessi - L'ABA spiegata a mia nonna - parte 10-

Prendere lo spazzolino
Prendere il dentifricio
Togliere il cappuccio dal dentifricio
Afferrare lo spazzolino con la mano sinistra
Afferrare il dentifricio con la mano destra
Spremere una piccola quantità di dentifricio sullo spazzolino
Aprire il rubinetto
Bagnare lo spazzolino sotto il rubinetto
Mettere lo spazzolino in bocca
Spazzolare i denti inferiori sul lato sinistro della bocca
Spazzolare i denti superiori sul lato sinistro della bocca
Spazzolare i denti inferiori sul lato destro della bocca
Spazzolare i denti superiori sul lato destro della bocca
Spazzolare i denti superiori davanti
Spazzolare i denti inferiori davanti
Sputare nel lavandino
Riempire il bicchiere di acqua (in questo caso il bicchiere é solitamente nel lavandono)
Mantenere in bocca l'acqua
Sputare l'acqua
Asciugare la bocca
Risciacquare lo spazzolino
Mettere a posto

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Il prompting ovvero l'arte dell'aiuto - L' ABA spiegata a mia nonna

Il rinforzo differenziale - L'ABA spiegata a mia nonna (parte 15 )

Lavo i denti in autonomia! - Studio Psicologia DSA Parma

Lavo i denti in autonomia, luciana auricchio maggio 3, 2018 apprendimento , bambini , bambino , cognitivo-comportamentale , comportamenti , pedagogia , potenziamento , psicologia.

Alle volte gli operatori o i genitori che si interfacciano con bambini con disabilità, si trovano di fronte a problemi relativi all’apprendimento di autonomie quotidiane.

Come faccio ad insegnargli a lavarsi i denti autonomamente? Come faccio a far sì che si infili i calzini autonomamente? Ce la farà? Etc.. Tutte domande a cui si fatica a dare una risposta o comunque per far prima si fanno le cose al suo posto..

Ma perchè non provare? Certo richiede fatica, ma sgravare un genitore o un operatore anche solo da piccole routine potrebbe essere funzionale per entrambi, il bambino impara ed il genitore resta da supporto in caso di necessità..

Ok, ma Come fare? Ecco alcuni consigli pratici per genitori ed operatori “addetti ai lavori”:

Per prima cosa costruisco una Task Analysis (suddivido il comportamento in vari step e costruisco una tabella dove esplicito ciascuno step). Di seguito vi diamo un prototipo di Task Analysis da poter utilizzare per insegnare lavare i denti …

Step0: Entrare in bagno

Step1: Prendere il dentifricio

Step2: Aprire il dentifricio

Step3: Poggiare il tappo del dentifricio

Step4: Prendere lo spazzolino

Step5: Mettere dentifricio sullo spazzolino

Step6: Poggiare dentifricio

Step7: Aprire l’acqua

Step8: Passare lo spazzolino sotto l’acqua

Step9: Chiudere l’acqua 🙂

Step10: Passare lo spazzolino Arcata esterna sup DX per 10 volte

Step11: Passare lo spazzolino Arcata interna sup DX per 10 volte

Step12: Passare lo spazzolino Arcata esterna inf DX per 10 volte

Step13: Passare lo spazzolino Arcata interna inf DX per 10 volte

Step14: Sputare

Step15: Passare lo spazzolino Arcata esterna sup SX per 10 volte

Step16: Passare lo spazzolino Arcata interna sup SX per 10 volte

Step17: Passare lo spazzolino Arcata esterna inf SX per 10 volte

Step18: Passare lo spazzolino Arcata interna inf SX per 10 volte

Step19: Passare lo spazzolino Davanti per 10 volte

Step20: Sputare

Step21: Aprire acqua

Step22: Sciacquare lo spazzolino sotto l’acqua e riporlo

Step23: Bere e sputare acqua per 2 volte

Step24: Chiudere acqua

Step25: Chiudere tappo dentifricio

Step26: Poggiare dentifricio

Step27: Asciugare bocca e mani

Gli esperti prendono il dato sull’esecuzione di ciascuno step, per costruire un grafico e monitorare l’andamento dell’apprendimento, ma il genitore può sgravarsi da questo compito 🙂

Però abbiamo ancora qualche consiglio importante:

Utilizzare sempre lo stesso linguaggio e lo stesso ordine di step ( Es. “Prendi il dentifricio”);
Inizialmente svolgere i vari step assistendo fisicamente il bambino (Es. prendere la mano del bambino e guidarlo nell’azione);
Ciascuno step ha bisogno di tempo per essere appreso quindi armiamoci di pazienza e per qualche volta guidiamo il bambino fisicamente per tutta l’esecuzione della procedura, successivamente una volta data l’istruzione (Es. “Prendi il dentifricio”) aspettiamo 1 secondo e se il bambino non lo svolge allora continuiamo con la guida fisica, altrimenti ha imparato a svolgere in autonomia quello step e così via… fino ad arrivare allo svolgimento completo della procedura “lavarsi i denti”.

L’autonomia è una conquista importante per un bambino con disabilità, alleggerisce la famiglia da impegni sempre più complessi ed abilita il bambino ad essere un individuo sempre più competente nel panorama multisfaccettato di bisogni e richieste da parte della società.

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©Studio Psicologia DSA Parma Developed by Fabio Prestini

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Come Lavare i Denti

Questo articolo è stato co-redatto da Tu Anh Vu, DMD . La Dottoressa Tu Anh Vu è una dentista iscritta all'albo che gestisce il suo studio privato, Tu's Dental, a Brooklyn (New York). La Dottoressa Vu aiuta bambini e adulti di tutte le età a superare l'ansia scatenata da odontofobia. Ha condotto ricerche finalizzate alla scoperta di una cura per il sarcoma di Kaposi e ha presentato il suo lavoro all'Hinman Meeting di Memphis. Ha conseguito una laurea di primo livello al Bryn Mawr College e si è laureata in Odontoiatria alla University of Pennsylvania - School of Dental Medicine. Questo articolo è stato visualizzato 144 206 volte

Lavare i denti non serve solo a rendere il sorriso più bianco e l'alito fresco: è importante per la tua salute in generale. Quando li spazzoli, infatti, rimuovi la placca, uno strato sottile di batteri che si deposita sui denti che provoca carie, problemi alle gengive e, se ignorata a lungo, ne causa persino la caduta. Ora sai perché è importante lavarli, ma se vuoi imparare come farlo nella maniera più efficace, prosegui nella lettura di questo articolo.

Usare gli Strumenti Giusti

Gli spazzolini elettrici sono un'ottima alternativa, se sei pigro e pensi in questo modo di essere più meticoloso nella pulizia. Tuttavia, anche uno spazzolino manuale può fare un lavoro preciso — è tutta una questione di tecnica.
Dovresti evitare assolutamente gli spazzolini con setole "naturali" di origine animale, perché possono essere ricettacolo di batteri.
Le ricerche dimostrano che tra le setole e il manico si annidano migliaia di microbi, che potrebbero causare infezioni.
Risciacqualo sempre dopo l'utilizzo e conservalo in posizione verticale e scoperto, affinché possa asciugarsi per l'uso successivo. In caso contrario favorirai la proliferazione batterica. [1] X Fonte di ricerca
Attualmente esistono dentifrici studiati per risolvere un'ampia gamma di problematiche dentali e gengivali come la carie, il tartaro, la sensibilità, la gengivite e i denti macchiati. Scegli il prodotto adatto alle tue esigenze o chiedi consiglio al tuo dentista.
Ricorda di usare il filo con delicatezza. Non farlo "scattare" tra i denti, perché potresti irritare le gengive . Inseriscilo delicatamente seguendo la curvatura naturale di ogni dente.
Se hai l'impressione che il filo interdentale sia scomodo da usare, oppure hai l'apparecchio ortodontico, prova gli scovolini. Sono dei piccoli bastoncini di legno o plastica che puoi inserire tra un dente e l'altro, ottenendo lo stesso risultato.

Padroneggiare la Tecnica

Se senti dolore mentre spazzoli, compra un dentifricio formulato per i denti sensibili.
Se ti annoi, lavati i denti mentre guardi la TV o mormori una canzone. Se li lavi per l'intera durata di una canzone sarai certo di aver fatto un lavoro accurato!

Terminare la Pulizia

Ad ogni modo, devi sapere che esiste un dibattito a tal proposito. Sebbene alcuni ritengano che risciacquare la bocca riduca l'efficacia dell'azione del fluoro, altri pensano che non convenga ingerire il dentifricio. Comunque, ci sono anche persone che detestano sentire il dentifricio in bocca dopo aver lavato i denti! Se tendi a soffrire di carie, sarebbe meglio non risciacquare o farlo solo in parte.
Alcuni studi hanno dimostrato che risciacquare la bocca dopo aver lavato i denti non influisce sull'efficacia del fluoro.
Se non puoi lavare i denti dopo avere mangiato, risciacqua la bocca con l'acqua per rimuovere le particelle di cibo.
Spazzola lingua e palato per un alito migliore.
Se le gengive sanguinano con facilità, potresti soffrire di gengivite. In tal caso, rivolgiti a un dentista. La gengivite, infatti, non solo causa la caduta dei denti e l'alito cattivo, ma anche le infezioni alle valvole cardiache. Procurati anche uno spazzolino dalle setole morbide.
Cerca di lavare i denti dopo avere bevuto caffè, tè e vino rosso. A lungo andare, infatti, queste bevande possono lasciare macchie permanenti sui denti.
La maggior parte della gente non riesce a modificare la propria routine di lavaggio. Prendi in considerazione la possibilità di spazzolare i denti in un luogo diverso, per evitare di ripetere gli stessi movimenti errati.
Spazzola più a lungo nelle zone problematiche.
Vai dal dentista ogni sei mesi per farti esaminare e sottoporti alla pulizia dei denti.
Ci sono degli spazzolini provvisti di timer che ti dicono per quanto tempo devi spazzolare. Sono utili per ricordarti di spazzolare aree diverse della bocca.
Aspetta una o due ore dopo ogni pasto prima di spazzolarti i denti.
Ricorda di lavarli dopo la colazione e prima di andare a letto. Assicurati di usare un collutorio alla fine!
Non usare una quantità eccessiva di dentifricio. Ne basta tanto quanto un pisello.
Stai attento a non usare degli spazzolini aggressivi, perché potrebbero danneggiare le gengive e favorirne la retrazione.
Strofina ogni dente con un movimento circolare continuo.
Il lavaggio dovrebbe durare tra i due e i tre minuti.
Gli spazzolini elettrici sono più comodi, ma in ogni caso, ricorda di avere buone abitudini di lavaggio.
Usa uno stuzzicadenti per eliminare le particelle di cibo tra i denti.
Passa il filo interdentale prima di spazzolare i denti.
Puoi usare un collutorio, ma accertati che sia senza alcool.
Cerca di lavarti i denti 3 volte al giorno. Se desideri dei denti VERAMENTE puliti dovresti lavarli dopo ogni pasto o spuntino.
Aspetta almeno 45 minuti dopo aver bevuto una bibita gassata o un succo di frutta, prima di spazzolarli. Queste bevande lasciano residui acidi sui denti e spazzolarli può danneggiare lo smalto.
Lavali almeno dopo la colazione e prima di andare a letto. Spazzolali dopo ogni pasto se possibile.
Cambia lo spazzolino ogni 3 mesi. Le setole usurate possono danneggiare le gengive.
Non spazzolare con troppa forza. Le gengive sono sensibilissime.
Non tralasciare la pulizia dei denti, poiché una cattiva igiene è causa di carie.
Se ingerisci una quantità eccessiva di dentifricio o collutorio, vai al pronto soccorso o chiama il centro antiveleni immediatamente.

Cose che ti Serviranno

Filo interdentale
Dentifricio
Collutorio (facoltativo)

wikiHow Correlati

Riferimenti

↑ http://www.mayoclinic.com/health/dental/DE00003

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Make Thinking Visible: A Cognitive Task Analysis Application in Dentistry

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HsingChi von Bergmann

The purpose of this study was to explore the use of cognitive task analysis to inform the teaching of psychomotor skills and cognitive strategies in clinical tasks in dental education. Methods used were observing and videotaping an expert at one dental school thinking aloud while performing a specific preclinical task (in a simulated environment), interviewing the expert to probe deeper into his thinking processes, and applying the same procedures to analyze the performance of three second-year dental students who had recently learned the analyzed task and who represented a spectrum of their cohort's ability to undertake the procedure. The investigators sought to understand how experts (clinical educators) and intermediates (trained students) overlapped and differed at points in the procedure that represented the highest cognitive load, known as "critical incidents." Findings from this study and previous research identified possible limitations of current clinical teac...

Mitchell J Lipp

Patient-centered care involves an inseparable set of knowledge, abilities, and professional traits on the part of the health care provider. For practical reasons, health professions education is segmented into disciplines or domains like knowledge, technical skills, and critical thinking, and the culture of dental education is weighted toward knowledge and technical skills. Critical thinking, however, has become a growing presence in dental curricula. To guide student learning and assess performance in critical thinking, guidelines have been developed over the past several decades in the educational literature. Prominent among these guidelines are the following: engage the student in multiple situations/exercises reflecting critical thinking; for each exercise, emulate the intended activity for validity; gain agreement of faculty members across disciplines and curriculum years on the learning construct, application, and performance assessment protocol for reliability; and use the same instrument to guide learning and assess performance. The purposes of this article are 1) to offer a set of concepts from the education literature potentially helpful to guide program design or corroborate existing programs in dental education; 2) to offer an implementation model consolidating these concepts as a guide for program design and execution; 3) to cite specific examples of exercises and programs in critical thinking in the dental education literature analyzed against these concepts; and 4) to discuss opportunities and challenges in guiding student learning and assessing performance in critical thinking for dentistry.

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Introduction. Dental education involves teaching and assessing the acquisition of verifiable domains that require superior psychomotor, communication, and cognitive skills. Evolving technologies and methods of assessment could enhance student's learning environment and improve tutor assessment experience. e aim of this study was to review the current body of research and evaluate the effectiveness of various methods of assessments in improving learning and performance in preclinical and clinical dental practice. Materials and Methods. A search strategy was implemented using electronic search in major databases. e following key terms, clinical skills, preclinical, dental students, and assessment, were included in the search. Two reviewers independently screened all the articles retrieved following very specific inclusion criteria. Results. e initial search generated 5371 articles and 24 articles were selected for review and data extraction. Cohen's kappa coefficient was used to measure interrater agreement and a score of 94.7% was obtained. Conclusion. Preclinical assessment is an effective tool for promoting skills transfer to clinical phase. Early psychomotor skills assessment is valuable. It allows early intervention in the learning process and assists in effective utilization of learning resources. Technology-enhanced assessment systems allow better patient simulation, enhance learning and self-assessment experiences, and improve performance evaluation. However, these systems serve as an adjunct to conventional assessment methods. Further research should aim at calibrating and integrating these systems to optimize students learning and performance.

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Task Analysis in ABA Therapy

Cute little boy drawing on the chalkboard

Welcome to our ABA therapy technique series where we explore the different techniques used by ABA therapists. In this article we will learn about Task Analysis.

Task analysis is an ABA technique where a therapist breaks complex tasks into easily manageable units. In this article we are going to examine what task analysis is, how it works, and how it is used in a clinical setting.

What Is Task Analysis

Task analysis is an essential technique used in ABA therapy . It consists in dividing activities into a series of easy steps. This way the activity will become less overwhelming and easier to learn for your child with autism.

The number of steps in a task will depend on the difficulty of the activity, as well as on your child’s age, level of functioning , and learning style.

How does it work?

An ABA therapist who uses task analysis will present a new activity as a logical progression of steps. For example, brushing teeth can be divided into the following tasks:

Pick up the toothbrush
Turn on the water tap
Rinse the toothbrush
Pick up the toothpaste tube
Place a dab of toothpaste on the toothbrush
Scrub the teeth gently
Spit the toothpaste into the sink
Place the toothbrush into the holder
Fill a cup with water
Rinse the mouth
Spit the water into the sink
Turn off the water tap

Your therapist will observe your child complete the target skill to get a clear idea of what level of support is needed for each step and identify the parts that may require additional instruction.

How Task Analysis Helps Children with Autism

Task analysis can be used to help children diagnosed with autism spectrum disorder master a wide range of multi-step skills. One of the greatest advantages of using task analysis in ABA therapy is teaching activities of daily living (ADLs), such as:

Washing hands
Brushing teeth
Bathing or showering
Using the toilet
Getting dressed
Preparing a meal
Making the bed
Performing household chores
Getting on public transport
Using a computer or tablet
Using the phone
Playing a sport
Money management
Time management

These activities are essential for promoting independence and building self esteem in children with autism.

Other skills and behaviors that your child can learn through task analysis include:

Communication and language skills
Social skills
Improving memory and attention
Academic skills

Chaining and Task Analysis

When using task analysis, ABA therapists will break down the skills that the child needs to learn into smaller steps. These steps are linked via chaining, which means that the child is required to complete each step before starting the next one.

Task analysis consists of three different types of chaining :

Forward chaining

Backward chaining, total task chaining.

Forward chaining refers to teaching steps of a task in chronological order. A therapist provides reinforcement each time your child masters a step.

Forward chaining is generally used with children who learn quickly and can perform at least some parts of the task independently.

Contrary to forward chaining, backward chaining skills are taught starting with the last step of the activity. The therapist will help your child with all the steps of the task except for the last one. Consequently, reinforcement is provided at the end of the sequence.

ABA therapists typically use the backward chaining technique when working with children on the spectrum who are less likely to follow the task sequence unprompted. This method is also effective for children who regularly attempt to insert other behaviors into the chain.

In total task chaining, the therapist teaches the steps of a task together and breaks down any problematic steps into simpler units. Unlike in forward and backward chaining, the child will receive reinforcement only after having completed the entire chain sequence.

Total task chaining is beneficial for children with autism who have the capacity to learn complex activities easily and who don’t need to do multiple attempts before they succeed in a task. However, if your child starts making too many errors within total task chaining, the therapist will revert to one of the other two chaining techniques.

ABA Therapy Resources

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Via Giglielmo Marconi, 35

+39 338 4580 272

Servizio Clienti

Imparare a lavare i denti

VINCI LA TUA SFIDA è il programma creato per te, programma con dimostrazioni e supporti visivi, in cui ti spiego dettagliatamente come raggiungere dei risultati con tuo figlio, con una percentuale altissima di successo.

Quante volte avrai pensato che è veramente difficile lavare i denti a tuo figlio autistico, ovviamente non conoscendole tecniche e le strategie che fanno alzare la tua probabilità di successo diventa difficile e poco motivante.

Ora puoi, accedendo al programma riceverai un intero programma dettagliato dove non dovrai fare altro che mettere in pratica alla lettera quello che c’è scritto.

Vuoi insegnare a tuo figlio a lavarsi i denti? Attraverso questo programma saprai finalmente cosa fare e come andare avanti giorno per giorno.

Programma scritto contenente: tutti i passaggi dalla desensibilizzazione allo spazzolino fino alla sfumatura del prompt.
2 Video modeling (uno con musica e un altro con la voce che accompagna)
Task analysis
La possibilità di contattarci per qualsiasi chiarimento (non sarai lasciato solo)

39,99 € 19,98 €

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Lessons from a pilot project in cognitive task analysis: the potential role of intermediates in preclinical teaching in dental education

Affiliations.

1 Dr. Walker is Assistant Professor, Educational Studies, Faculty of Education, The University of British Columbia; and Dr. von Bergmann is Associate Professor, Education Research, Faculty of Dentistry, The University of British Columbia.
2 Dr. Walker is Assistant Professor, Educational Studies, Faculty of Education, The University of British Columbia; and Dr. von Bergmann is Associate Professor, Education Research, Faculty of Dentistry, The University of British Columbia. [email protected].
PMID: 25729022

Keywords: cognitive task analysis; dental education; educational methodologies; peer teaching; preclinical education; psychomotor skills.

Publication types

Research Support, Non-U.S. Gov't
Cohort Studies
Decision Making
Dental Restoration, Permanent / methods
Dentistry, Operative / education
Education, Dental*
Faculty, Dental
Pilot Projects
Psychomotor Performance
Students, Dental
Task Performance and Analysis*
Teaching / methods*
Videotape Recording

TASK ANALYSIS

22,00 € IVA esclusa

IL KIT COMPRENDE: ANDARE AL BAGNO: 11 carte plastificate cm 10×13 LAVARSI I DENTI: 11 carte plastificate cm 10×13 LAVARSI LE MANI: 6 carte plastificate cm 10×13 PREPARARE UN PANINO: 9 carte plastificate cm 10×13 FARE UNA SPREMUTA: 8 carte plastificate cm 10×13 Supporto plastificato con spirale cm 10,5×96

Descrizione

Andare al bagno – lavarsi le mani – lavarsi i denti – fare un panino – fare una spremuta.

La maggior parte dei bambini con difficoltà di apprendimento, rileva difficoltà a portare a termine i compiti più complessi e difficili da eseguire. La Task analysis (analisi del compito) è una metodologia basata sulle evidenze e ha fornito indicazioni per favorire l’apprendimento a eseguire un compito che richiede molti passaggi. L’utilizzo di un’analisi del compito è un modo per insegnare abilità complesse come: imparare a lavarsi le mani, i denti, fare un panino, fare una spremuta. La presentazione di una serie d’immagini è un supporto valido e semplice per fare acquisire al bambino le varie fasi in maniera ordinata e soprattutto fargli raggiungere l’autonomia. Acquisire l’abilità di lavarsi le mani attraverso un task analysis (step-by-step), permette di segmentare un compito complesso in piccoli passi, seguendo in maniera sequenziale, con concatenamento anterogrado e retrogrado, l’ordine dei compiti attraverso una sequenza d’immagini.

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How to Conduct a Task Analysis

Before starting development on a new eLearning project, it’s important to make sure you’ve collected and analyzed all the information used to justify the creation of an eLearning course in the first place. One of the ways you do this is by conducting a needs analysis to determine the root cause behind the gap in performance and whether or not eLearning (or any learning intervention) is the right solution. Another method of analyzing the learning need is by conducting a task analysis, which can be helpful when you’re scoping your eLearning project or creating an action map to design a proposed training solution.

A task analysis is a process of analyzing a specific task to determine how it’s completed, step-by-step.

A task analysis is a process of analyzing a specific task to determine how it’s completed, step-by-step. While this might seem pretty straightforward, a task analysis can get pretty detailed. When done correctly, a thorough task analysis will be broken down into procedures, primary tasks, and subtasks.

But, why should you consider conducting an eLearning task analysis in the first place? Well, the results of a task analysis can be used to determine many different variables about your project. First, a task analysis can help you ensure your learning and performance objectives align with the actual tasks your learners need to perform. And second, a task analysis can help you determine the total scope and complexity of what you need to teach your learners. This information can help you decide whether or not additional learning interventions are required to accomplish the desired learning goal.

Here are three simple steps for conducting a task analysis.

Step One: Identify the Primary Procedure

The first step for conducting a task analysis is to identify the primary procedure your learners are expected to perform. When identifying the primary procedure, you want to avoid being too broad, which could result in performing a task analysis on something that should actually be separated out into multiple procedures.

For example, if you were conducting a task analysis on a financial auditor, performing an analysis on their responsibility of “auditing financial records” would likely be too complex. The reality is that this responsibility is comprised of multiple, individual procedures (i.e., completing the daily finance audit, organizing and sending audit results to the audit committee, submitting the monthly tax report to the Internal Revenue Service, etc.).

In this case, we’ll look at the procedure of “completing the daily finance audit.”

Step Two: List the Main Tasks

The second step in conducting a task analysis is to identify and list the main tasks for completing the primary procedure. Similar to identifying the primary procedure, you don’t want to be too broad or too specific.

When listing the main tasks, and the subtasks, use action verbs to describe each task. For example, for our procedure of “completing the daily finance audit,” it might look something like this:

Download the daily finance report.
Review the daily finance report for inaccuracies.
Report inaccuracies to the corporate finance auditor.

Step Three: List the Subtasks

The third and final step for conducting a task analysis is to break the main tasks into subtasks. The subtasks are where you start getting granular with the level details of each task.

Using the first main task from our example of “completing the daily finance audit;” here’s what the final task analysis might look like, broken down into subtasks:

Download the daily finance report: a. Login to the finance operating mainframe. b. Click the Run Daily Report button. c. Click the Download Daily Report button.

The Bottom Line

Once you’ve successfully completed your task analysis, you should have a holistic, step-by-step outline of what’s involved in completing an identified procedure, which you can use in designing your learning intervention. What other tips can you share about conducting a task analysis? Share them by commenting below!

Hi, I’m Tim Slade, and I’m a speaker, author, and founder of The eLearning Designer's Academy. Having spent the last decade working to help others elevate their eLearning and visual communications content, I have been recognized and awarded within the eLearning industry multiple times for my creative and innovative design aesthetics. I’m also a regular speaker at international eLearning conferences, a LinkedIn Learning instructor, and author of The eLearning Designer’s Handbook.

How to Create an Instructional Design Document

The Truth About Learning Styles | The eLearning Designer's Academy by Tim Slade

This is such a great tip! Thanks, TIm.

Here’s something I like to do. Once I know what learners will need to be able to do when they have completed the course/training, I work backward. I ask; What do they need to know or practice in order for that to be realized? Then, I take those pieces and ask the same about each of those pieces. Keep in mind your target audience’s prior knowledge, experience, and familiarity with the topic or tasks. Keep working backward and chunking things down until you get to the point where the next thing they need to know or practice is something they already know or do. Then, you’ve discovered the all the things in between that need to be included in the training to fill in the missing gaps/pieces so they can get to the goal of the proposed training.

Thanks, Philip! I’m in total agreement with your backwards design approach. Thanks for sharing!

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Task Analysis: An Individual, Group, and Population Approach, 3rd Ed. (Adoption Review)

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The ability to competently analyze an occupation, activity, or task is a fundamental skill of the occupational therapy practitioner. Task analysis, the process of analyzing the dynamic relation among a client, a selected task, and specific contexts, is a critical clinical reasoning tool for evaluating occupational performance. This new edition of this foundational text guides occupational therapy practitioners in using task analysis to understand clients and their ability to perform specific, purposeful activities.

Aligned with the Occupational Therapy Practice Framework, Task Analysis expands the understanding of clients to include individuals, groups, and populations and how task analysis applies to each. Occupational therapy practitioners increasingly serve clients at the group and population levels, which is reflected in updated chapters.

This edition aims to provide students and practitioners with a clear understanding of how task analysis applies to everyday occupational therapy practice. Each chapter contains assignments to challenge students and readers and promote learning, and case examples promote real-world application. An extensive Client Profile and Task Analysis Form provides a template for the clinical world, and examples of its use are included throughout the text. The form, assignments, case examples, and AOTA official documents are downloadable.

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Front Matter i 2
Dedication iii 4
Contents v 6
Acknowledgments vii 8
About the Authors ix 10
List of Figures, Tables, Exhibits, Case Examples, and Assignments xi 12
Introduction xv 16
Part I. Domain and Process of Occupational Therapy 1 20
1. Historical Perspective: Intervention Through Activity 3 22
2. Occupational Therapy Services: A Distinct Approach 13 32
3. Domain and Dimensions of Occupational Therapy 27 46
4. Occupational Therapy Process 37 56
5. Occupational Therapy Service Delivery to Individuals, Groups, and Populations 55 74
6. Care Planning: Needs Analysis and Use in Consultation 77 96
Part II. Occupation and Intervention Strategies 87 106
7. Occupations Across the Lifespan 89 108
8. Play as Occupation 111 130
9. Education as Occupation 145 164
10. Activities of Daily Living as Occupation 159 178
11. Adolescence and Emerging Adulthood 171 190
12. Adulthood: Maintaining Meaningful Lifestyles 183 202
13. Older Adults: Transitions for Successful Aging 197 216
14. Healthy Communities 209 228
Appendix A. Client Profile and Task Analysis Form 225 244
Appendix C. Occupational Therapy’s Role in Sleep 237 256
Appendix D. Occupational Therapy in the Promotion of Health and Well-Being 241 260
Subject Index 253 272
Citation Index 259 278
Appendix B. Position Paper: Purposeful Activity 233 252

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Foundations for Designing User-Centered Systems pp 309–333 Cite as

Methodology I: Task Analysis

Frank E. Ritter 4 ,
Gordon D. Baxter 5 &
Elizabeth F. Churchill 6
First Online: 01 January 2014

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Task analysis (TA) is a useful tool for describing and understanding how people perform particular tasks. Task analyses can be used for several purposes ranging from describing behavior to helping decide how to allocate tasks to a team. There are several methods of TA that can be used to describe the user’s tasks at different levels of abstraction. We describe some of the most commonly used methods and illustrate the use of TA with some example applications of TA. TA is widely used but when using TA there are considerations to keep in mind such as the fact that many approaches require an initial interface or specification, and that many do not include context multiple users or ranges of users. These considerations help describe where and when TA can be successfully applied and where TA will be extended in the future.

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Ritter, F.E., Baxter, G.D., Churchill, E.F. (2014). Methodology I: Task Analysis. In: Foundations for Designing User-Centered Systems. Springer, London. https://doi.org/10.1007/978-1-4471-5134-0_11

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Cognitive task analysis and workload classification

Automation can be utilized to relieve humans of difficult and repetitive tasks in many domains, presenting the opportunity for safer and more efficient systems. This increase in automation has led to new supervisory roles for human operators where humans monitor feedback from autonomous systems and provide input when necessary. Optimizing these roles requires tools for evaluation of task complexity and resulting operator cognitive workload. Cognitive task analysis is a process for modeling the cognitive actions required of a human during a task. This work presents an enhanced version of this process: Cognitive Task Analysis and Workload Classification (CTAWC). The goal of developing CTAWC was to provide a standardized process to decompose cognitive tasks in enough depth to allow for precise identification of sources of cognitive workload. CTAWC has the following advantages over conventional CTA methodology:

• Integrates standard terminology from existing taxonomies for task classification to describe expected operator cognitive workload during task performance.
• Provides a framework to evaluate adequate cognitive depth when decomposing cognitive tasks.
• Provides a standard model upon which to build an empirical study to evaluate task complexity.

Graphical abstract

Specifications table

Introduction

Automation is progressively taking over roles once allocated to humans, presenting opportunities to relieve the burden of strenuous and repetitive tasks, and to create more efficient systems. As a result, new supervisory roles are being created where humans actively observe autonomous systems and provide input when needed. These new supervisory roles, where operators are continuously receiving system output and responding accordingly, are highly variable, existing across many domains, and ranging in complexity. This variability in complexity can influence the performance of the supervisory tasks. It is not fully understood how to evaluate and optimally design these new roles to maximize human and system performance.

Cognitive task complexity, due to its unobservable nature, is not particularly well understood. Cognitive tasks of varying complexity can lead to varying degrees of cognitive workload in humans. Cognitive workload is a latent construct that describes the effort required by the working memory to perform a cognitive task [2] . Workload can be measured in many ways, including self-reporting [3 , 4] , performance measures (accuracy and timing of tasks) [5 , 6] , behavioral observations [7] , and neurophysiological measures such as pupil response [8 , 9] , heart rate variability [10] , EEG [11 , 12] , and core temperature [13] .

Cognitive workload can influence human performance in different ways. Excessive cognitive workload has been associated with poor human performance and error [4 , 14 , 15] , while moderate levels of elevated cognitive workload has been linked to increased performance [16 , 17] . One recent study found that large, sudden spikes in cognitive workload corresponded to decreased performance, whereas consistent, elevated cognitive workload corresponded to increased performance [18] . Regardless, understanding the level of workload that operators experience in complex systems is critical to optimize the system for human performance. A method to classify tasks based on cognitive workload can provide a basis for evaluation. This work provides a methodological approach to accomplish this. Before tasks can be classified, an approach to decompose a high-level system goal into meaningfully distinct sub-tasks is required.

Task analysis is an analytical process in which a skill, movement, or cognitive process is decomposed into sub-tasks that a system operator must complete to accomplish the high-level goals of the system [19] . Task analysis is a useful process because it facilitates the identification of task subcomponents which can be evaluated or modified independently. It is a hallmark tool in human factors research, and has been used in many applications including product design, instructional design and training, function allocation, and error and workload assessment [20] . In this paper, we are primarily interested in performing task analysis on cognitive tasks, known as cognitive task analysis (CTA).

CTA focuses on the underpinning mental framework, thought processes, and knowledge behind the performance of a task [1] . It can be used to identify hidden and ineffective cognitive strategies as well as tasks that induce high cognitive demand. It can also be used as a baseline model for task optimization to maximize human performance [21 , 22] . Approaches to CTA are very diverse, with researchers having identified over 100 different varieties [1] . Five steps common to most CTA approaches are: 1) Collect preliminary knowledge; 2) Identify knowledge representation; 3) Apply focused knowledge elicitation methods; 4) Analyze and verify acquired data; and 5) Format results for intended application [1] . Approaches are typically classified by the knowledge elicitation approach, and generally includes 1) Observation and interviews; 2) Process training; and 3) Conceptual techniques [23] . CTA has been used in a variety of domains, including autonomous vehicle display design [24] , electronic health record design [25] , instructional design [26 , 27] , and design of medical training programs [28] .

In this paper, a new approach to CTA is discussed that includes several improvements over existing approaches. Existing CTA methodologies do not represent cognitive tasks in adequate cognitive depth and lack standardization. Cognitive depth permits precise identification of sources of cognitive workload. Standardized terminology to describe cognitive tasks can facilitate comparison between analyses and provide a theoretical framework for continued validation. Additionally, few methods have attempted to integrate CTA results into empirical research and use that data to perform task-specific cognitive workload analysis. Chan & Kaufman [29] utilized standard terminology from Bloom's taxonomy to classify tasks, however no empirical validation of the classification was performed. Liang et al. [30] performed CTA and rated the cognitive workload demand of tasks using the VACP rating scale [31] and empirically validated the ratings with data obtained via NASA-TLX. While this work did contain a validation of standardized classifications for task cognitive workload, metrics for validation were limited to subjective survey data collected post hoc. An approach for task cognitive workload validation that integrates objective (accuracy, timing) and neuro-physiological (e.g. pupil dilation) data into the validation process could provide additional robustness. This paper discusses an approach to CTA that uses standardized terminology from existing cognitive and psychomotor taxonomies to describe operator cognitive workload and a process to empirically validate and analyze task-specific cognitive workload.

The following section introduces a CTA methodology to predict operator cognitive workload entitled Cognitive Task Analysis and Workload Classification (CTAWC). The steps of this methodology are as follows:

1) Traditional Task Analysis – The task or process of interest is decomposed into basic actions the user performs to achieve the end goal. This is performed iteratively with help from users and expert stakeholders.
2) Cognitive Task Analysis (CTA) – Cognitive tasks required of the user are defined for each traditional task identified in the previous step using cognitive and psychomotor taxonomies. Tasks are gradually decomposed to a satisfactory level.
3) Experimental Validation – A controlled experiment is designed to simulate the task and measure cognitive workload for classified tasks of interest. Experimental and theoretical workload are statistically compared.

This methodology is introduced in the context of its prior application in a companion paper that includes detailed experimental results [18] . The use case scenario is a control room monitoring task from the perspective of the operator, which will be introduced first.

Use case scenario

A use case scenario is a representation of a real-world process, generalized for the sake of analysis. It is a model of how the parts of a system behave and interact [32] . Developing a scenario is important for CTAWC because it sets the groundwork to cognitively decompose activities and serves as a guide for experimentation and simulation. The scenario specific to this work is control room operation. Control room operators are required to monitor the status of autonomous and semi-autonomous systems over long periods of time while remaining vigilant to respond or intervene, if necessary. In cases where a response becomes necessary, the operator is required to find and analyze salient information, make a decision regarding that information, and respond, typically through some form of physical (e.g., press a button) or sensory (e.g., voice command) system input. In cases where accuracy and time-sensitivity are critical for effective and safe operation, the workstation environment should be designed to minimize operator cognitive workload and maximize task performance. CTAWC provides a baseline model of workload for the task and opens opportunities to evaluate changes in workload in response to design changes. This application was demonstrated in [18] and will be used to support explanations of methodological steps in subsequent sections.

Procedural task analysis

The original and simplest form of task analysis is called sequential, or procedural task analysis (PTA) [33] . This is the first step of CTAWC. As the name implies, tasks are identified and represented in a sequential manner, which defines the process flow. Decision points, where multiple trajectories of a process are formed, are also commonly integrated into the PTA. Typically, tasks outlined in a PTA are physical or motion-based tasks. In other words, tasks describe what the human is “doing”, in contrast to what the human is thinking (an important addition which is introduced in the next section). There are many ways to perform a PTA and the correct way is highly dependent on the application [34] . This section describes just one approach.

The first step of the task analysis is to identify the overarching goal of the task to be analyzed. This defines the outer-most bounds of the analysis and provides a starting place for decomposition. This should be established at the beginning of the CTAWC process with input from key stakeholders of the system being analyzed.

From there, the overarching task can be decomposed into physical sub-tasks and processes. These should describe the physical actions that take place to achieve the end goal of the system. Once again, this should be done with collaboration from stakeholders who have first-hand experience operating in the system of interest. The process is iterative and can be approached as a continuous, open discussion on whether the tasks identified reflect the true nature of the system. This process is referred to as requirements elicitation.

For the control room monitoring scenario, project sponsors from the Naval Air Systems Command (NAVAIR) served as key stakeholders in the requirements elicitation process. A continuous dialog with these key personnel helped to identify the core physical processes necessary for the monitoring task and produced the following basic process flow applicable to most control room operations: 1) Operator passively monitors feedback from the system; 2) Operator receives an alert or indication that some new procedure must be performed; 3) Operator uses input devices (keyboard, mouse) to perform procedures; and 4) Operator monitors the response of the system. A graphical version can be seen in Fig. 1 .

Procedural task analysis for control room monitoring task.

Cognitive task analysis

CTA uses the basic process flow from the prior step as input and identifies the human cognitive actions required to perform all steps of the task. This involves hierarchically decomposing the task into cognitive actions and may involve filling in gaps between tasks as well.

Decomposition structure

The structure of this decomposition follows a hierarchical task analysis format [35 , 36] , which provides additional depth for each high-level task with a plan to dictate how to traverse the levels. This structure and the associated plan can account for both concurrent and serial tasks, representing parallel and sequential cognitive processing, respectively.

The scope of cognitive actions should include low-level processing such as recalling basic facts and ideas up to high-level processing such as evaluating criteria and decision-making. Both observable and non-observable tasks can be included. Observable tasks are primarily those in the psychomotor domain related to movement and coordination of the body. Non-observable tasks are memory, decision-making, and sensory processes. Specifics of sub-tasks should be tailored for the use case scenario.

Tasks can be written in many formats. Often a tabular or bulleted list is used where each sub-bullet level represents a level of the decomposition. If special instructions are required for performance of tasks, such as the order, this can be interspersed at the end of levels. For example:

A graphical or flowchart representation may be desirable in some cases. If the relationships between tasks or the order that tasks are performed is particularly complicated, it may be easier to represent the task analysis as a flow chart. Further, stakeholders who are not familiar with task analysis may find a graphical presentation more intuitive or easier to understand.

Evaluating decomposition depth

A common question that arises when performing task analysis is how deep to go with the decomposition. If the decomposition isn't deep enough, then tasks may be too broad and difficult to precisely evaluate. If the decomposition is too deep, there is risk of the analysis exploding into too many variables and task evaluation becoming cumbersome. Additionally, if the goal is to empirically evaluate decomposed tasks, tasks that are too granular may be difficult to isolate/observe in practice. Of the two, it is better to err on the side of additional depth as one can always return to the prior level of depth.

More importantly, the appropriate depth depends on the goals of the analysis. If the researchers have a hypothesis defined prior to the analysis, then the tasks should be decomposed to the point such that the hypothesis can be tested. For example, returning to the control room scenario, if a researcher wanted to test whether control room operators experience elevated cognitive workload when searching for a button to respond to an alarm, then the analysis should be at least deep enough to isolate that individual visual search task.

Defining cognitive actions and task syntax

To facilitate the identification of cognitive actions for each previously identified process, cognitive and psychomotor taxonomies can be used. One of the novel contributions of this methodology is the integration of taxonomy-driven classifications of cognitive tasks to model operator cognitive workload. CTAWC utilizes Bloom's taxonomy of the cognitive domain [37] and Harrow's taxonomy of the psychomotor domain [38] to do this modeling. Bloom's taxonomy is a six-tiered model for classification of cognitive skills and is described in Table 1 , where each tier corresponds to increased cognitive complexity, thus providing a structure to identify tasks of increasing workload. Likewise, Harrow's taxonomy is a six-tiered model for classification of psychomotor skills and is described in Table 2 .

Bloom's Taxonomy listed in order of increasing cognitive complexity.

Harrow's Taxonomy listed in order of increasing psychomotor complexity.

This methodology asserts that these taxonomy classifications can be used to identify and predict workload experienced by operators during cognitive tasks. Bloom's taxonomy primarily addresses non-observable actions, starting at the lowest level of cognitive function in memory-based tasks (Knowledge). As the levels increase, the conscious control required to execute the task also increases, with each higher level composed of the lower level tasks. For example, to perform an Application task, one must first remember specific facts or ideas (Knowledge), understand the recalled information (Comprehension), and then apply it to a novel situation. Harrow's taxonomy, focuses primarily on observable tasks, moving from lower levels of complexity (Reflexive Movements) to higher levels (Non-Discursive Communication). Harrow's taxonomy also considers non-observable sensory tasks (Perceptual Abilities). Combined, Bloom's and Harrow's taxonomy provide a comprehensive categorization of human tasks that can be used to understand how cognitive workload and complexity is represented in a series of actions. The taxonomies also provide a list of verbs ( Tables 1 and and2) 2 ) that can be used, in addition to their synonyms, to develop action words corresponding to each cognitive task.

While originally intended for and most commonly applied to evaluating educational objectives [39 , 40] , CTAWC integrates Bloom's and Harrow's taxonomy into a task analysis framework for assessing operator cognitive workload. There are few past examples of using these taxonomies in conjunction with task analysis [29 , 41] , and to our knowledge there have been no attempts to connect the taxonomy levels to cognitive workload through empirical data.

Returning to the procedural tasks identified prior, one can begin to decompose tasks into cognitive tasks, using Bloom's and Harrow's taxonomy as a guide. A portion of the control room monitoring process is shown in Table 3 for a single task block of the original PTA. The process moves from left to right in the table.

CTA for PTA task “Receive alert or indication a new procedure is required”.

In the best-case scenario, cognitive tasks will fit neatly into a single taxonomy level. If a task does not fit into a single taxonomy level, this may indicate a need to decompose tasks further. This process can be used as an additional approach to determine if the task analysis reached an adequate depth. If a task cannot be classified neatly into a taxonomy level, and one does not wish to decompose tasks any further, then there are a few other options. Multiple taxonomy levels can be matched to individual tasks, however this may complicate the model and hinder interpretation. Another approach is to use the highest taxonomy level (highest level of cognitive complexity) applicable to the task, the logic being that the operator will experience cognitive workload at least as much as that taxonomy level implies. For example, if a task requires the use of comprehension and evaluation then, one could assume, that the operator will experience cognitive workload at the level evaluation tasks typically generate. This approach assumes that there isn't an interacting effect between multiple taxonomy levels occurring, which may not always be the case in all scenarios.

Experimental validation protocol

After completing the CTA, an empirical study can be designed to validate the decomposition. This section discusses a protocol for designing a study to validate the assumed hierarchy of task complexity based on Bloom's and Harrow's taxonomy.

Experimental research questions

The first task is to define experimental questions based on the decomposed tasks and the goals of the research. In general, the objective will be to investigate differences in performance between tasks. Determining what tasks to investigate and the level of granularity to define hypotheses is the initial challenge. This will depend on resource availability, as constraints will limit the number of hypotheses that can be feasibility tested. Also important are the goals of the analysis. If specific tasks are more important to investigate than others, then those should be prioritized and targeted.

Depending on the complexity of the overarching tasks, there may be many more tasks than can be feasibly tested in a laboratory experiment due to resource and recruitment burden. In the companion paper [18] , the lowest-level of the decomposition resulted in 29 individual tasks, which is too many to control in an experiment. There are several practical considerations related to the study length and resources. Experimental run time is a critical metric, with subject recruitment rate having a strong relationship to the amount of time the subject must devote to the experiment. Additionally, it is problematic from a safety and ethics perspective to keep subjects in an experimental facility for more than 90 min without a break, which compromises continuous biosensing and calibration of equipment. Resources such as wireless devices and other equipment may have limitations for run time, requiring power source and system memory replacements mid-experiment. For the control room study, the target population consisted of University students, therefore timing was a critical factor, as many students have scheduling limitations.

To address the previous resource limitations, instead of trying to measure each individual task, one could opt to move up a level in the decomposition and create a hypothesis around all the classifications applied to each task on that level. The full CTA for the control room study can be seen in Table 4 . It was hypothesized that the tasks classified with the highest taxonomy levels will result in the highest levels of cognitive workload, which aligned with experimental evidence [18] . The resulting task model was a sequence of four tasks, where Task 2 (corresponding to Task 4 in Table 4 ) and Task 3 (corresponding to Task 5 in Table 4 ) contained Synthesis and Analysis from Bloom's taxonomy and were hypothesized to be higher workload tasks. Task 1 (corresponding to Tasks 1–3 in Table 4 ) and Task 4 (corresponding to Tasks 6–7 in Table 4 ) only contained low-level tasks from Bloom's taxonomy and tasks from Harrow's taxonomy, and it was therefore hypothesized that operators would experience less cognitive workload during these tasks. Therefore, the resulting hypothesis was to test whether there was a significant difference in operator performance and cognitive workload between each of the 4 tasks.

Resulting cognitive task analysis originally developed in [16] .

One could take an alternative perspective and make a hypothesis about the interaction or cumulative effect of multiple taxonomy levels occurring during the same task. This was not the approach taken in the accompanying work [18] , but there is room for future work investigating this idea. In either case, an approach for empirically validating these hypotheses is discussed in the next sections. Discussed first are validation metrics for human performance and cognitive workload.

Human performance measures

Experimental validation of taxonomy classifications requires performance metrics. Objective and subjective measures of human performance can be utilized to encourage study robustness through a mixed method experimental approach. Objective metrics can measure workload and performance directly using accuracy or timing, and indirectly with biosensors for neurophysiological data correlated with workload. Subjective metrics use participant feedback to directly quantify perceptions of workload. This method suggests the use of both to validate task workload classifications for a more robust study. Discussed next are the criterion used to select the objective and subjective measures for the experimental validation study.

For objective, indirect measures of human performance, there are several factors to consider when selecting the biosensing hardware. Most biosensors are wearables and may be influenced by movement of the wearer. Body movement can cause issues with data quality in biosensors, such as with electroencephalography (EEG) headsets [42] , [43] , [44] . In these cases, additional efforts to filter movement artifacts may be required [45] . Biosensors may also interfere with the wearers ability to perform a task. As well as being susceptible to motion artifacts, biosensors such as a pulse oximeter worn on the finger can make it difficult for subjects to physically interact with a system using their hands [46] . The selected biosensors should not inhibit the subject's ability to move and complete the tasks necessary for the experiment.

Another factor to consider when choosing a biosensor is whether to buy a commercial off the self (COTS) product or to custom build a system. Purchasing a COTS biosensor may provide the opportunity to review other users’ experiences, come with software to assist with data collection and processing, and provide access to technical support. Downsides of a purchased biosensor include limited control over the data and cross-manufacturer software integration difficulties. Proprietary software may perform data calculations that cannot be altered or examined due to intellectual property restrictions. Building a custom biosensor bypasses these limitations but requires additional development, debugging, system integration, and validation time. A lab-built biosensor requires research into which parts to use and should be benchmarked against commercial biosensors to test accuracy and reliability. Depending on time constraints, this may be infeasible.

For the control room study, subjects were required to turn their heads to view multiple screens and type responses to cues on those screens. This eliminated the use of biosensors whose data quality is significantly impacted by subject motion. The need for subjects to type also disqualified the use of biosensors that attach to the hand. Ultimately, pupillometry via COTS biosensors (SMI VR ETG eye-tracking glasses) ( Fig. 3 A) was selected to indirectly measure subject workload. Additional detail on the eye tracking system setup is provided in Section 2.5.2. Pupil response has been demonstrated as a reliable indirect measure of cognitive workload [47] , [48] , [49] . Further, these sensors are designed to allow the wearer to move their head and minimally influence the data.

Hardware used during the study. A. SMI eye tracking glasses B. Lab built vibrotactile bracelet C. VR CAVE system.

Subjective feedback from participants can reinforce objective data and provide direct insights about a system operator's experience. For workload assessment, pre-validated instruments such as the Subjective Workload Assessment Technique (SWAT) [50] and NASA Task Load Index (NASA-TLX) [51] can be applied to many simulations. These generalized assessment tools have the advantage of being well validated across many domains, however, they may not meet the time constraints of the experiment or provide the context specificity desired. For the control room study, participant feedback was required at several intervals within the simulation. This required participants to be able to provide feedback quickly, with minimal disruption to the flow of the study. These requirements were not satisfied by the existing survey instruments. For this reason, a custom survey was developed. This provides the dual benefit of being able to design the survey to the needed length and tailor questions to specifically evaluate each task of interest.

The medium for administering the survey should be considered as well. Paper and pencil are likely the most reliable medium, however, this requires handoffs between researchers and participants and introduces manual administrative and data input tasks. If the simulation requires interaction with a computer, then a digital survey format is advantageous. For the control room study, participants were already interacting with a screen, therefore the survey was implemented with a batch file code that could be executed remotely.

Experimental setup

There are many logistical considerations when designing a human performance simulation. This section discusses how the study requirements were carefully integrated within the limitations of the hardware and software available.

Simulation requirements

Scenario development was conducted with thorough planning and input from several sources. Stakeholders were interviewed, and a literature review on control room design was performed to ensure the simulation tasks and environment aligned with the real-world tasks. Stakeholder feedback is an important aspect of the iterative design process and confirms that what is being designed conforms to stakeholder expectation [52] , [53] , [54] , [55] . Feedback was iteratively gathered from the project stakeholders to ensure simulation realism. A primary goal of the screen layout, communicated by project stakeholders, was to be generalizable to many monitoring scenarios. Therefore, the replication of a specific monitoring and control software was avoided. In addition, several critical systems had to be simultaneously accessible to the operator. These requirements led to the development of a quadrant layout providing information on system health, location, real time navigation (front facing camera), and communication ( Fig. 2 ). A mock-up of the control room was presented to project sponsors from the NAVAIR Human Systems Performance Division. The sponsors were asked to provide feedback on simulation features, including the number of screens that should be included and the realism of displayed information.

Finalized four quadrant layout used in the simulation. Screens display the following information: 1) health of the UAV (see through dials/bar graphs); 2) communications system (through which the participant can issue commands); and both a 3) forward and a 4) downward facing terrain camera.

In addition to stakeholder input, control room and design standards, scholarly literature, and existing control room images were reviewed to help improve the accuracy of the control room design. Feedback in simulated environments should be designed carefully to elicit realistic responses from participants. In the control room simulation, the form of the multimodal sensory feedback relied heavily on a review of these sources. Department of Defense standard MIL-STD-1472F [56] , Department of Transportation standard DOT HS-812–360 [57] , and American National Standards Institute standard ASTM F116 –95a [58] were used to inform the design of visual, audio, and tactile feedback, respectively. Visual, tactile, and audio alarms are used in a variety of safety critical systems including control rooms [59 , 60] , automobiles [57 , 61 , 62] , and ships [63] . Visual alarm cues can involve icons appearing on the screen, changing colors [58] , and flashing [56] . For visual cues in this experiment, the colors yellow and red were used to denote non-critical or critical alarms, respectively. Several standards recommend the use of the color red to gain an individual's attention in an emergency and yellow as a cautionary warning [56 , 58 , 64] .

Tactile feedback was provided to the participants using a custom vibrotactile wristband ( Fig. 4 , ,3B). 3 B). The vibrotactile bracelet was composed of an Arduino Mini, a mini vibrating disc motor, a small solderable breadboard, a 3D printed case, and a sweat wristband. Arduino hardware was used due to the flexibility of customization of the hardware and code. The Arduino Mini was used to keep the wrist bracelet small and lessen the chance of it interfering with subject movement. A sweat band was picked as the wearable because it would be able to stretch to fit on a variety of wrist sizes and make the donning/doffing process easier. Tactile feedback was used due to its presence in everyday objects such as cell phones and in automobile and plane safety systems. The feedback frequency used was around 180 Hz to 200 Hz since it is a similar range used in cell phones [65 , 66] . The tactile feedback was applied for milliseconds at a time to get an individual's attention [57 , 62 , 67 , 68] . This form of feedback is unique because it uses a sensory channel that is not already being used to observe the environment. Sense of sight and sound can be overwhelmed in monitoring tasks because there are multiple pieces of information competing for attention.

Vibrotactile bracelet built for the experiment. A. An inside view of the components B. Final product.

Two types of audio alarms were used in the study: beep and voice. Both were designed to be loud enough to be heard over the ambient noise of the Cave Automatic Virtual Environment (CAVE) system running the experiment, and to utilize the surround sound system. The beep was designed to be distinct to not get lost in background noise programmed into the experiment [69] . Voice cues were used because they have been shown to improve a subjects ability to respond accurately [70 , 71] . The voice used in the experiment was that of a monotone woman. Evidence has shown that a monotone voice can increase response time when used in alerts [58 , 72] . It is widely agreed that the voice should be mature and that the message should be succinct, relay the criticality of the alarm through tone or word choice, and be repeated multiple times [56 , 58 , 64] .

Hardware setup

In the companion paper [18] , a simulation was built in a virtual reality (VR) CAVE ( Fig. 3 C) consisting of three walls on which simulations can be projected by Barco Galaxy 6 Classic+ projectors. It is possible that this simulation could have been built for a head-mounted display (HMD), however the use of the CAVE environment allowed participants to interact with other physical artifacts, such as a keyboard for simulation input, that can provide additional immersion. Additionally, it does not require donning of additional hardware, which an HMD requires. Six Tannoy system 600 speakers provided surround sound for audio feedback. The simulation was intended to replicate a UAV control room. Advanced Realtime Tracking (ART) motion capture cameras, consisting of 4 cameras placed in the 4 corners of the CAVE, and Dtrack software were used to track the subjects head in space and monitor the screens they were looking at during the simulation. Six motion capture markers on the side of the SMI eye tracking glasses, 3 markers per side, were used to create a rigid body that Dtrack can use to calculate the subject's head position throughout the experiment. Fig. 5 shows a participant engaged in the simulation with equipment donned.

Participant operating the UAV simulation.

In addition to the VR and tracking infrastructure, several elements were considered for data acquisition. The hardware set-up should be optimized to minimally impact the simulation. This includes the advanced charging of electronics. Back-up equipment and batteries should be available when possible. A standardized and repeatable procedure for setting up equipment is critical to be established and practiced prior to running subjects. This will help minimize the time required for set-up and will help to eliminate variability between participants. In the control room simulation, participants were required to don several pieces of equipment, including eye-tracking glasses and a vibrotactile bracelet. Participants were aided as much as possible when donning the equipment and given explicit instruction when direct aid could not be given.

For eye-tracking hardware, it should be verified that ambient light and light from the testing or simulation environment have minimal impact on pupil response. Ambient lighting should not be changed throughout the experiment, or between experiments. If lighting in the experimental set-up must change, then a light meter should be used to verify that the change in luminance is minimal. If there are significant changes in luminance throughout the experiment, this could confound pupil response results. For the control room experiment, luminance testing was performed with the Urceri MT-912 Light Meter ( Fig. 6 ). This was necessary to verify that lighting changes from the CAVE simulation would not influence pupil response. To do this, the maximum and minimum lighting conditions for the simulation were identified. Luminance measurements were taken at eye level height, facing the center and 4 corners of each CAVE screen under each condition. The measured luminance during each condition was virtually identical, and it was concluded that changes in lighting during the simulation should have minimal influence on participant pupil response.

Urceri MT-912 light meter used for luminance testing.

The experimental layout is also critical. If wireless electronics can be used, this is ideal because it minimizes the likelihood of tripping and equipment accidently becoming disconnected, as well as providing a non-clustered research environment. This said, if possible, wired back-ups should be available. In practice, wireless connectivity is not always as reliable as hardwired equipment, which is particularly critical when data is being logged in the millisecond range. Reliability issues with a wireless keyboard were encountered during the control room study that required the substitution of a wired keyboard.

Software development

Unity software was used to create the simulation. Specifically, Unity 5.3.5 was used for software compatibility with getTeal3D, a Mechdyne CAVE rendering software. A review of control room images revealed that control rooms often use a quadrant-based layout to display information. The 3D objects used to create the four screens were created from scratch or from assets that could be found in the Unity store.

The simulation monitors were composed of a rectangular prism with interactive objects overlaid. The terrain that the UAVs flew over was created with a terrain tool built in Unity ( Fig. 7 ). The UAV asset was imported from the Unity asset store. Two camera views were used to show the UAV flying over the terrain; one attached to the front of the UAV and one looking down on the UAV. Both cameras were set to move with the UAV as it moved over the various terrains. A short video of the UAV flying through the terrains was captured and embedded in the simulated monitor. The dials on the health screen reflected the health of the UAV throughout the experiment and was designed to change values in response to the alarm status. For example, if the critical fuel alarm was triggered, then the fuel dial would move to empty.

Sample of simulation terrain.

Communications was the only screen that allowed direct subject interaction. Information gathered from the standards documents were used to guide the presentation of information. The communications screen changed color to attract the subject's attention when an alarm was triggered [56] . As mentioned earlier, the colors yellow and red were used to denote non-critical or critical alarms per standards documentation [56 , 58 , 64] . If the subject was running a version of the alarm scenario that required tactile feedback, then the vibrotactile bracelet would activate when the communications screen lit up. If the subject was running the voice audio version of the scenario, then they would hear a monotone, female voice stating which alarm was triggered (e.g., “Low fuel”). Ambient office sounds were imported into the simulation to distract participants and further enhance simulation realism. Office sounds were recorded in a noisy office where machines and background speech can be heard.

External devices were programmed into the simulation when possible. The SMI glasses were not integrated into the simulation software due to the device being controlled by a secondary device; a Samsung Galaxy Note 4. For user input and response, a standard QWERTY keyboard was used. It was selected because tactile keyboards are commonly used for a multitude of tasks in modern UAV control rooms. Additionally, the keyboard was selected as the main input device because it provided a simple, familiar, and instantaneous medium for input. Keyboard input was not subjected to the frame rate drops and the lag the simulation might encounter. Subjects could select the desired screen (1–4) using the F1-F4 keys ( Fig. 8 ). Once subjects selected the correct screen, keys F9-F12 could be used to select which alarm to acknowledge. F-keys not utilized as part of the experiment were occluded from subject view to minimize mistyping. The communications screen then would ask the user if further action was required. Subjects were required to type “0” for non-critical alarms or “1” for critical alarms and press the “Enter” key to log their response.

The keyboard layout for simulation command input.

Training material

Prior to performing the simulation, it was necessary for each participant to be trained on the scenario and simulation tasks they would perform. A slide deck was developed to facilitate training ( Fig. 9 ). The training material included a brief background on the context of the scenario. This was kept brief to not overwhelm participants with information irrelevant to performing the tasks at hand. Details were provided about the sensors and equipment to be worn, as well as steps that can be taken by participants to minimize influence on the sensor data. This included instructions to avoid talking, touching the head or face, and touching the devices. Further information was included regarding the tasks the participants would perform, including an embedded video demonstration.

Sample of participant training slides.

Prior to the simulation, the participant would be seated in front of an interactive whiteboard with the slide deck loaded. Participants would be instructed to advance through the slides, and to ask the study proctor questions as needed. It is critical for researchers to contribute minimal influence to the training protocol across participants. Differences in training could confound results.

Data analysis

Procedures for pre-processing and analysis of data are heavily dependent on the performance measures and equipment selected. The steps used for pre-processing simulation data and the tools used for analysis in [18] are briefly discussed here.

Preprocessing of data

The bulk of the data preprocessing was performed on eye tracking data. Eye tracking data is known for being noisy and needing substantial cleaning. Corrective procedures can be used to ensure data is minimally influenced by noise and confounding factors. Preprocessing steps for pupil response data included temporally aligning data with the simulation, removing noise, ensuring data fits within known physiological limits, and adjusting data with a baseline correction.

Preprocessing began with aligning the eye tracking data with the simulation start time. Control of the SMI glasses could not be integrated into the simulation, requiring that they be started before the simulation. The simulation was executed as quickly as possible following starting the glasses, but lag would often interfere with the simulation starting time. The recordings of the experiment were manually reviewed to denote how much time passed between starting the glasses and the simulation start.

A MATLAB script was created prior to the study to perform the rest of the preprocessing. Removing noise is a common practice when analyzing data [73] , [74] , [75] . The removal of noise can minimize unwanted influence due to random fluctuation and confounding factors (e.g. removing pupil data that is outside the biological range) [76] . The code scanned the data and removed data points that were outside of the possible biological range for pupil diameter. Anything less than 2 mm or greater than 8 mm was removed [77] . Any subjects who had more than 50% of their data removed after this was removed from analysis.

Baseline correction of data is used to facilitate comparison between participants and has been shown to correct for random fluctuations in pupil data [74] . Baseline correction is done by taking data collected from a period of rest and subtracting the data to be analyzed by an average value during the rest period. Subtractive, as compared to divisive, baseline correction has been found to be less susceptible to distortions in the data [74] . The baseline data consisted of pupil values from 2 s prior to the first alarm of each simulation.

Data analysis tools

To answer the core hypotheses identified in 2.4.1, several statistical analyses were performed. Regardless of the type of performance or workload data collected, this general analysis should be applicable. In the control room simulation, the goal of the analysis was to determine if there was a statistical difference in performance measures for Tasks 1–4. Each task can be thought of as an independent variable, and each performance measure can be treated as a dependent variable. As such, a model can be created for each performance measure. For the control room study, performance measures included pupil response data and survey response data. Pupil response was a continuous variable, therefore linear regression was used. Likewise, survey response was a binary variable, therefore logistic regression was used. As always, it is important to check standard model assumptions required for fitting a linear model.

In the case of [18] , four simulations were performed with four task sequences each. It was hypothesized that participant performance may increase as time progresses (i.e. a learning effect). Because simulations and trials were spaced in approximately equal time segments for all participants, each could be treated as a continuous control variable in the models. The continuous assumption may not hold in all cases. If the periods of time are not equally spaced and exact time is not recorded, then it may be better to treat time periods as categorical or ordinal variables.

With categorical independent variables, regression coefficients will only provide effects with respect to the reference category. Multiple comparisons will need to be performed to identify differences between all tasks. As more comparison are made, the probability of finding false positives significantly increases. As such, a correction to the p-value should be applied to reflect a more conservative estimate. Many procedures exist, such as the Tukey test and Bonferroni correction, and most statistical programming packages will have built in functions to perform them [78] .

Finally, as an additional step, correlation between performance variables can be investigated. This can provide insight as to whether indirect measures of performance serve as good indicators of direct performance. In these cases, direct measures of performance can be modeled as dependent to indirect measures. By including each task and each indirect performance variable as independent variables, the effect of each indirect measurement can be estimated independent of the task type. This important because each task type will likely have an inherent amount of time needed or accuracy required, independent of participant performance. In [18] , some evidence was found to support task time having an association with pupil response and survey response.

Conclusions

Optimizing a system for maximum human performance requires an understanding of the cognitive tasks required of the user. CTA provides a process for isolating the distinct mental processes performed by system operators. This paper describes an approach to CTA that integrates cognitive and psychomotor taxonomies for predicting cognitive task workload. This approach was demonstrated on a control room monitoring task and demonstrated its ability to discriminate between high and low task complexity. This framework could be potentially applied to any system where unobservable human action plays a significant role in system operation. Future work should include efforts to validate this approach in different settings. Future work should also seek to further demonstrate the discriminating power of the taxonomy classifications. Currently, only “high” and “low” workload was discriminated. Demonstrating that individual levels of the taxonomies can be used to discriminate cognitive workload experienced could provide further validity. Ensuring that systems operate effectively and safely requires models of operator workload to provide a framework for system optimization. This work provides an approach for creating and validating those models.

Declaration of Competing Interest

The Authors confirm that there are no conflicts of interest.

Cornerstone of Task Leadership Starts with Task Analysis

By Jack Murphy

There is no limit to the effort organizations and leaders put into improving organizational leadership theory and practice. The age-old challenge of collective effort – often referred to as project or program management; task leadership – is continually scrutinized, refined, and rethought. In the industrial age, organizational leadership kicked into high gear; in the information age, the art and science of organizational leadership are evolving at warp speed. Consider the proliferation of methodologies introduced over the last 50 years to improve collective efforts across a wide range of governmental, industrial, and creative enterprises:

Management By Objective

Work Breakdown Structures

Agile, Scaled Agile

This organizational leadership evolution reflects the boundless human capacity for creativity and drives improvement to meet today’s challenges.

Interestingly, regardless of the approach taken, at the heart of any successful organization’s efforts is task leadership – organizing and empowering teams to accomplish a common goal . Successful leaders consistently demonstrate several fundamental skills. These are defined in three simple categories:

Task Analysis – understanding the task at hand, being able to visualize the desired end-state, whether it is a product, a new organization, or a new order of things.

Task Organization – Organizing the team and its resources (including time) to achieve the task at hand, economically and efficiently.

Task Completion – Leading the team through the effort, which entails communicating, empowering, guiding, and adjusting individual and collective energies while remaining focused on the desired end state.

In this three-article series, we dive into each of these cornerstone activities of task leadership. Each of these skills requires the organizational leader to bring a range of tools, techniques, and processes to the task regardless of team member composition, resources, or the task itself.

Working towards the end state with task analysis

Leaders are challenged to establish and communicate a shared vision of the end state. Before any resources – including people and time – can be reasonably committed to the effort, stakeholders, task leadership, and team members must establish “what right looks like.” Even with seasoned, competent team members, the organization of the task analysis process requires fundamental leadership skills.

“ My greatest strength as a consultant is to be ignorant and ask a few questions.” – Peter Drucker

The Task Analysis Working Group has defined task analysis as “the study of what an operator (or team of operators) is required to do, in terms of actions and/or cognitive processes to achieve a…goal,” in their book A Guide To Task Analysis . This is an admittedly concise definition, but task analysis can be a daunting intellectual exercise.

Skilled task leaders can envision the desired end state and break it down into workable terms for the team. Even the most well-thought-out strategies are nothing more than interesting discussions until broken down into workable components. It is equally essential that the leader be able to both visualize and communicate “what right looks like.” This usually involves the ability to:

Understand the stakeholders – these may be customers, constituencies, leadership teams

Understand the product or goal, with measurable outcomes

Understand the organization’s capabilities

Develop a broad approach, bound by the “iron triangle” of delivery, cost, and schedule

Rapidly integrate to become a contributing member of the team as quickly as possible

The task analysis process requires a blend of understanding, curiosity, and communication techniques. Truly skilled organizational leaders will blend “fresh eyes with experience,” viewing the challenge with the proverbial open mind but understanding the industry, market, and the broader organizational mission and culture. They will also be prepared to engage the stakeholders at the earliest possible moment in the lifecycle of the project to:

Ask leading questions

Suggest general approaches and methodologies

Articulate a vision that confirms “what right looks like”

Trusted advisors

Engagement is most successful when there is a level of trust and familiarity between the stakeholders and the organizational leader. The most effective organizational leaders historically enjoy a “trusted advisor” relationship with stakeholders. They know that an understanding of the end state is critical before transitioning to the task estimation step and may employ a wide range of techniques to validate this vision. These include pragmatic methodologies, organization-specific task analysis tools or templates, or simply outlining a vision and submitting it to stakeholders for their validation. Ultimately the skilled organizational leader knows that this critical step must be complete before initiating task estimation.

Task estimation

While task estimation is often a mix of science and imagination, the contemporary organizational leader can leverage a wide range of task analysis and estimation tools and enablers. The truly skilled leader has a toolbox of multiple techniques and knows which one is most appropriate for the task at hand.

Understanding and integrating the stakeholder’s decision-making processes, resource constraints, and strategic goals will factor in this selection, but task estimation is a fundamental task leader skill, often honed over time and informed by both success and failure.

At this stage, the skilled organizational leaders’ greatest deliverable is known by many names – work breakdown structure, project plan, product roadmap and so on – but it will be the first articulation to the team of the desired end state.

The following case study considers the various aspects of task analysis and applies them to a real-world success story.

Case Study – Accelerated Platform Migration.

The data management business unit of a large manufacturing organization realized that it would need to transition rapidly from an existing commercial off-the-shelf platform to an updated data storage technology. The migration itself would have been challenging enough with ample time and people resources; unfortunately, neither was available for this decision.

Task analysis impact

Our task leader quickly organized a conference that included key stakeholders, including business decision-makers, supporting team leaders, and most importantly, the team members who would ultimately be responsible for carrying out the migration tasks. Over a two-day series of meetings, the task leader engaged each stakeholder group individually and collectively confirmed what success looks like. Using simple questions such as “How will the successful migration impact your short, intermediate, and long-term business goals?” and “What are end-user access requirements [to the data] during the migration?” ensured everyone knew “what right looked like.”

While the task leader was engaging key stakeholders, he asked the migration team leads to assess the scope of the data to be migrated to gain a measurable metric for estimating the level of effort.

The task leader then gathered the entire team and, with stakeholder priorities and requirements laid out and confirmed and the initial scope estimate available, engaged all the members to solicit their input for two critical decisions:

Selection and application of an estimation technique (analogous estimation was selected)

Confirmation of a broad approach.

Note: while the task leader suggested several options to the team on how to approach the task, he was careful to remain open to a variety of approaches, and as long as these did not violate stakeholder requirements and overall data migration goals, he encouraged and supported team development of the final migration plan.

Concurrent to this discussion, the task leader continually compared technical requirements with team capabilities to ensure resources and skills matched the emerging general approach.

Finally, as the team agreed to an overall approach that met the iron triangle of delivery, cost and schedule, the task lead translated this approach into a written plan to communicate to stakeholders at this point in the task analysis process. The task leader had a particularly challenging communication requirement. He had to :

Obtain stakeholder commitment for resources

Clearly define risks and assumptions in terms that can be understood by the stakeholders

Set reasonable expectations (for both stakeholders and team members)

As the task lead communicated the key elements of this approach, he also began articulating a vision of success to the team, instilling confidence that the selected approach was feasible while even thinking through the next step – organizing the team for success.

In our next article in the series, we look at task organization , “organizing the team and its resources (including time) to achieve the task at hand and economic inefficient manner.”

La task analysis

Sep 10, 2014

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Cuneo, 30 Marzo 2011. La task analysis. Francesca Vinai, Consulente per le attività educative. [email protected] [email protected]. « In quel momento apparve la volpe. “ Buon giorno ” disse la volpe.

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Cuneo, 30 Marzo 2011 La task analysis Francesca Vinai, Consulente per le attività educative. [email protected] [email protected]

«In quel momento apparve la volpe. “Buon giorno” disse la volpe. “Buon giorno” rispose gentilmente il piccolo principe, voltandosi: ma non vide nessuno. “Sono qui” disse la voce “sotto il melo …” “Chi sei?” domandò il piccolo principe “sei molto carino …” “Sono una volpe” disse la volpe”

“Vieni a giocare con me” le propose il piccolo principe “sono così triste … ” “Non posso giocare con te” disse la volpe “non sono addomesticata.” …. “Che cosa vuol dire addomesticare? ” … “La mia vita è monotona. Io do la caccia alle galline e, gli uomini danno la caccia a me. Tutte la galline si assomigliano, e tutti gli uomini si assomigliano. E io mi annoio perciò. Ma se tu mi addomestichi, la mia vita sarà come illuminata.

Conoscerò il rumore dei passi che sarà diverso da tutti gli altri. Gli altri passi mi fanno nascondere sotto terra. Il tuo mi farà uscire dalla tana, come una musica. … “Che bisogna fare?” Domandò il piccolo principe. “Bisogna essere molto pazienti … in principio tu ti siederai un po’ lontano da me, così, nell’erba. Io ti guarderò con la coda dell’occhio

e tu non dirai nulla. Le parole sono una fonte di malintesi. Ma ogni giorno potrai sederti un po’ più vicino. ” (…) Il piccolo principe tornò l’indomani. “Sarebbe stato meglio ritornare alla stessa ora”, disse la volpe, “se tu vieni per esempio tutti i pomeriggi alle quattro dalle tre comincerò a essere felice. (…) Ma se tu vieni non si sa quando, io non saprò mai a che ora prepararmi il cuore. Ci vogliono iriti”

“Cos’è un rito?” “E’ quello che fa un giorno diverso dagli altri giorni, un’ora dalle altre ore”.» Il piccolo principe Antoine de Saint - Exupèry

Cos’ è la task analysis? ?

Task analysis La task analisys si riferisce alla descrizione dell’obiettivocomportamentale o meta comportamentale che ci siamo prefissati attraverso l’analisi del compito, sia nelle diverse fasi che lo compongono in sequenza sia nei prerequisiti necessari a evidenziare le diverse abilità basilari per eseguire correttamente il compito. Meazzini,1997 8

Task analysis Descrizione dettagliata di ogni comportamento che normalmente viene emesso per il raggiungimento dell’obiettivo comportamentale. Sequenza di fasi. 9

Task analysis 1. Descrizione dell’obiettivo comportamentale o meta. 2. Descrizione di ogni comportamento o fase che si emette nell’esecuzione del compito. 3. Valutazione iniziale delle capacità dello studente. 10

Task analysis La task analisys è una procedura comportamentale che consiste nel scomporre il compito nella sequenza di singoli step che lo costituiscono. Abilità complesse (ad es., lavarsi le mani) vengono scomposte in sotto unità più semplici (ad es., tirare su le maniche) e da insegnare una alla volta. 11

Ad esempio: “lavare i denti …”

Prendere il tubetto di dentifricio • Svitare il tappo di dentifricio • Mettere il tappo del dentifricio sul lavandino • Prendere lo spazzolino • Premere il tubetto di dentifricio • Mettere il dentifricio sul lavandino • Mettere lo spazzolino in bocca • Strofinare i denti (destra sopra, destra sotto …. )

9. Togliere lo spazzolino dalla bocca 10. Appoggiare lo spazzolino sul lavandino 11. Aprire l’acqua fredda 12. Prendere il bicchiere 13. Mettere l’acqua nel bicchiere 14. Fare un sorso d’acqua 15. Sciacquare 16. Sputare l’acqua

17. Svuotare il bicchiere d’acqua 18. Risciacquare il bicchiere d’acqua 19. Sciacquare lo spazzolino 20. Mettere lo spazzolino nel bicchiere 21. Chiudere l’acqua 22. Mettere il tappo al dentifricio 23. Mettere il dentifricio nel bicchiere 24. Asciugare le mani

Task analysis Definizione obiettivo Definire i singoli task Scomposizione ulteriore in singoli task Ordinare i task secondo una “traiettoria”

Lavare le mani …..??

Task analysis 18

Task analysis • Scomposizione di un compito nei suoi vari step può sembrare un procedimento semplice. • Attenzione: • Valutazione iniziale livello di abilità della persona • Pensare “concretamente” al compito da scomporre • Sperimentare task analisys prima di utilizzarla con la persona Task Analisys diverse a seconda della persona. 19

Insegnamento anterogrado: procedura secondo cui si insegna una catena di comportamenti partendo dal primo step. Insegnamento retrogrado: procedura secondo cui si insegna una catena di comportamenti partendo dall’ultimo step.

Task analysis • Frasi scritte • Immagini • Frasi scritte + immagini 24

Fetta biscottata con la marmellata Prendere una fetta biscottata Prendere la marmellata Prendere un piatto Prendere un coltello Mettere la fetta biscottata sul piatto Prendere il coltello Spalmare la marmellata sulla fetta biscottata con il coltello Chiudere il barattolo della marmellata Mettere via la marmellata Mettere il coltello nel lavandino

Task analysis Differenti tipologie: • Frasi scritte • Immagini • Frasi scritte + immagini 26

Esempio: LAVARE I DENTI. 27

Esempio: LAVARE I DENTI. 32

LAVO I DENTI Spazzolino Dentifricio Apro l’acqua Lavo i denti Chiudo l’acqua

Esempio: LAVARE I DENTI. 34

Lavo i denti Prendo:

Metto il dentifricio Metto lo spazzolino sotto l’acqua

Lavo i denti Lavo i denti

Sputo l’acqua Risciacquo i denti

Asciugo la bocca

Esempio: LAVARE LE MANI ED IL VISO. 40

LAVO LE MANI Sapone Chiudo l’acqua Asciugo le mani Apro l’acqua Lavo le mani LAVO IL VISO Chiudo l’acqua Bagno la manopola Lavo il viso Sapone Asciugo il viso Apro l’acqua

Esempio: METTO IL PIGIAMA. 42

METTO IL PIGIAMA

Esempio: USO DEL BAGNO. 45

Associazione un futuro per l’autismo – ONLUS 48

Esempio: USO DEL BAGNO. 49

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COMMENTS

Task Analysis Lavarsi i Denti: La Guida Definitiva per una Perfetta
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Il chaining: insegnare i comportamenti complessi
Una task analysis può essere realizzata anche con dei simboli o fotografie. Qui vediamo una task analysis del lavaggio delle mani Esistono due procedure per insegnare una catena di comportamenti: il concatenamento anterogrado (in avanti) ed il concatenamento retrogrado (all'indietro) .
Lavo i denti in autonomia!
Di seguito vi diamo un prototipo di Task Analysis da poter utilizzare per insegnare lavare i denti …. Step0: Entrare in bagno. Step1: Prendere il dentifricio. Step2: Aprire il dentifricio. Step3: Poggiare il tappo del dentifricio. Step4: Prendere lo spazzolino. Step5: Mettere dentifricio sullo spazzolino. Step6: Poggiare dentifricio.
TRAINING SU LAVAGGIO DENTI
Lavaggio denti realizzato attraverso pittogrammi ARASAAC e immagini miste. Utilizzo del metodo task analisys.#neuropsicomotricità#training#taskanalisys
LAVAGGIO DENTI
LAVAGGIO DENTI. Check list lavare i denti. IMMAGINI Lavaggio denti. PECS lavaggio mani. SIMBOLI lavaggio denti.
Help Teach Toothbrushing with Task Analysis to Break the Steps Down
To help you understand the toothbrushing task, I will provide a step-by-step analysis. Gather your toothbrush and toothpaste. Wet your toothbrush and put a pea-sized amount of toothpaste on the bristles. Start brushing at the gum line using a gentle circular motion. Brush the outer and inner surfaces of the teeth.
Come Lavare i Denti: 14 Passaggi (con Immagini)
Spazzola delicatamente seguendo un movimento breve e verticale, o circolare. Non spazzolare con un movimento orizzontale, questo è un errore frequente. 3. Pulisci tutti i denti. Spazzola un po' per volta, muovendoti delicatamente da una parte all'altra della bocca e concentrandoti per 12-15 secondi su ogni zona.
PDF Tecniche insegnamento nella pedagogia speciale
Un esempio di task analysis Attività relative alle autonomie (cura del sé) Chaining o concatenamento dopo che il soggetto ha esercitato le risposte (sotto-obiettivi) uno ad uno il procedimento prevede la concatenazione di tutte le risposte in ordine, l'ordine deve essere riprodotto in modo sequenziale e adeguato al compito Es. lavarsi le mani
(PDF) Make Thinking Visible: A Cognitive Task Analysis Application in
Figure 2. Screenshot of cognitive task analysis video Note: The larger intraoral view was filmed by a camera mounted on the bridge of the clinician's eyeglasses. The smaller frontal clinician operating view was filmed using a video camera. These two films were merged to create a cognitive task analysis video.
Task Analysis in ABA Therapy
Task analysis is an essential technique used in ABA therapy. It consists in dividing activities into a series of easy steps. This way the activity will become less overwhelming and easier to learn for your child with autism. The number of steps in a task will depend on the difficulty of the activity, as well as on your child's age, level of ...
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Lessons from a pilot project in cognitive task analysis: the potential
The purpose of this study was to explore the use of cognitive task analysis to inform the teaching of psychomotor skills and cognitive strategies in clinical tasks in dental education. Methods used were observing and videotaping an expert at one dental school thinking aloud while performing a specific preclinical task (in a simulated ...
Skill components of task analysis
Introduction. Some task analysis (TA) methods are used to understand, discover, and represent a task in terms of goals and subgoals, for example, Hierarchical Task Analysis (HTA, Annett and Duncan 1967) and Goal-Directed Task Analysis (GDTA, Endsley et al. 2003).Although widely described in procedure and underlying skills (e.g., Crandall et al. 2006; Kirwan and Ainsworth 1992), there is still ...
TASK ANALYSIS
La Task analysis (analisi del compito) è una metodologia basata sulle evidenze e ha fornito indicazioni per favorire l'apprendimento a eseguire un compito che richiede molti passaggi. L'utilizzo di un'analisi del compito è un modo per insegnare abilità complesse come: imparare a lavarsi le mani, i denti, fare un panino, fare una ...
Principles of Task Analysis and Modeling: Understanding Activity
Task analysis is a cornerstone of User Centered Design (UCD) approaches (Diaper 2004), aiming to collect information from users about the work they are doing and the way they perform it.According to (Johnson 1992), "any Task Analysis is comprised of three major activities; first, the collection of data; second, the analysis of that data; and third, the modeling of the task domain " (p. 165).
How to Conduct a Task Analysis
Step Two: List the Main Tasks. The second step in conducting a task analysis is to identify and list the main tasks for completing the primary procedure. Similar to identifying the primary procedure, you don't want to be too broad or too specific. When listing the main tasks, and the subtasks, use action verbs to describe each task.
MI LAVO I DENTI
MI LAVO I DENTI. MI LAVO I DENTI. wet toothbrush Brushing Teeth rinsetoothbrugh toothpaste on brush brush teeth spit in sink. Author. HP. Created Date. 4/6/2020 9:50:23 AM.
Task Analysis: An Individual, Group, and Population Approach ...
Abstract. The ability to competently analyze an occupation, activity, or task is a fundamental skill of the occupational therapy practitioner. Task analysis, the process of analyzing the dynamic relation among a client, a selected task, and specific contexts, is a critical clinical reasoning tool for evaluating occupational performance.
Methodology I: Task Analysis
Abstract. Task analysis (TA) is a useful tool for describing and understanding how people perform particular tasks. Task analyses can be used for several purposes ranging from describing behavior to helping decide how to allocate tasks to a team. There are several methods of TA that can be used to describe the user's tasks at different levels ...
Cognitive task analysis and workload classification
Decomposition structure . The structure of this decomposition follows a hierarchical task analysis format [35,36], which provides additional depth for each high-level task with a plan to dictate how to traverse the levels.This structure and the associated plan can account for both concurrent and serial tasks, representing parallel and sequential cognitive processing, respectively.
Cornerstone of Task Leadership Starts with Task Analysis
These are defined in three simple categories: Task Analysis - understanding the task at hand, being able to visualize the desired end-state, whether it is a product, a new organization, or a new order of things. Task Organization - Organizing the team and its resources (including time) to achieve the task at hand, economically and efficiently.
PPT
Task analysis La task analisys è una procedura comportamentale che consiste nel scomporre il compito nella sequenza di singoli step che lo costituiscono. Abilità complesse (ad es., lavarsi le mani) vengono scomposte in sotto unità più semplici (ad es., tirare su le maniche) e da insegnare una alla volta. 11.

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Task Analysis: An Individual, Group, and Population Approach, 3rd Ed. (Adoption Review)

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Methodology I: Task Analysis

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Cognitive task analysis and workload classification

Graphical abstract

Introduction

Use case scenario

Procedural task analysis

Cognitive task analysis

Decomposition structure

Evaluating decomposition depth

Defining cognitive actions and task syntax

Experimental validation protocol

Experimental research questions

Human performance measures